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1 Simple Rules to Remember When Working with Indexes Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, California Abstract SAS users are always interested in learning techniques related to improving data access. One way of improving information retrieval from a SAS data set or table is to create and use an index. An index consists of one or more columns that are used to uniquely identify each row within a table. Functioning as a SAS object containing the values in one or more columns in a table, an index may be defined as numeric, character, or a combination of both. This presentation will emphasize the rules that users should know when creating and using indexes to make information retrieval more efficient. Introduction Given the large number of books and articles on SQL and SQL-related topics, how strange it is not to find more material related to indexes and their impact on WHERE clause processing. Certainly, these topics deserve additional attention in order to assist SQL users achieve a greater understanding in applying these powerful features in their database applications. Indexes are designed to improve the speed in which subsets of data are accessed. Rather than physically sorting a table (as performed by the ORDER BY clause or the BY statement in PROC SORT), an index is designed to set up a logical data arrangement without the need to physically sort it. This has the advantage of reducing CPU and memory requirements. It also reduces data access time when using WHERE clause processing. This paper presents elements essential to achieving a better understanding of indexes and their effect on WHERE clause processing. Tables Used In Examples The data used in all the examples in this paper consists of a selection of movies that I ve viewed over the years, along with its actors. The Movies table consists of six columns: title, length, category, year, studio, and rating. Title, category, studio, and rating are defined as character columns with length and year being defined as numeric columns. The data stored in the Movies table is illustrated below. MOVIES Table The data stored in the ACTORS table consists of three columns: title, actor_leading, and actor_supporting, all of which are defined as character columns. The data stored in the Actors table is illustrated below. 1

2 ACTORS Table Understanding Indexes What exactly is an index? An index consists of one or more columns in a table to uniquely identify each row of data within the table. Operating as a SAS object containing the values in one or more columns in a table, an index is comprised of one or more columns and may be defined as numeric, character, or a combination of both. Although there is no rule that says a table must have an index, when present, they are most frequently used to make information retrieval using a WHERE clause more efficient. To help determine when an index is necessary, it is important to look at existing data as well as the way the base table(s) will be used. It is also critical to know what queries will be used and how they will access columns of data. There are times when the column(s) making up an index are obvious and other times when they are not. When determining whether an index provides any processing value, some very important rules should be kept in mind. An index should permit the greatest flexibility so every column in a table can be accessed and displayed. Indexes should also be assigned to discriminating column(s) only since query results will benefit greatest when this is the case. Simple Rules to Know About Indexes When an index is specified on one or more tables, a join process may actually be boosted. The PROC SQL processor may use an index, when certain conditions permit its use. Here are a few things to keep in mind before creating an index: If the table is small, sequential processing may be just as fast, or faster, than processing with an index Do not create more indexes than you absolutely need If the page count as displayed in the CONTENTS procedure is less than 3 pages, an index may no be warranted If the data subset for the index is not small, sequential access may be more efficient than using the index If the percentage of matches is 15% or less then an index may be appropriate The costs associated with an index can outweigh its performance value an index is updated each time the rows in a table are added, deleted, or modified. Sample code will be illustrated next to demonstrate the creation of simple and composite indexes using the CREATE INDEX statement in the SQL procedure. 2

3 Creating a Simple Index A simple index is specifically defined for one column in a table and must be the same name as the column. Suppose you had to create an index consisting of movie rating (RATING) in the MOVIES table. Once created, the index becomes a separate object located in the SAS library. SQL Code CREATE INDEX RATING ON MOVIES(RATING); SAS Log Results CREATE INDEX RATING ON MOVIES(RATING); NOTE: Simple index RATING has been defined. Creating a Composite Index A composite index is defined for two or more columns in a table and must have a unique name that is different than the columns assigned to the index. Suppose you were to create an index consisting of movie category (CATEGORY) and movie rating (RATING) in the MOVIES table. Once the composite index is created, the index consisting of the two table columns become a separate object located in the SAS library. SQL Code CREATE INDEX CAT_RATING ON MOVIES(CATEGORY, RATING); SAS Log Results CREATE INDEX CAT_RATING ON MOVIES(CATEGORY, RATING); NOTE: Composite index CAT_RATING has been defined. Index Entries and Pointers An index file is stored in the same SAS library as its associated data file. Having the same name as its data file, it is represented as a separate entity known as an INDEX member type. An index file contains entries organized hierarchically with entries being connected by pointers and organized in ascending order. Each entry contains a unique value corresponding to the column s frequency distribution and one or more unique observations, referred to as the record identifier (RID). Space that is occupied by deleted values are automatically reclaimed and reused by the index. A sample index containing entries representing the index file for the movie rating (RATING) is illustrated below. Value RID G 21 PG 2, 9, 14, 15, 18, 19 PG-13 3, 7, 8, 10, 12, 13, 22 R 1, 4, 5, 6, 11, 16, 17, 20 3

4 Index Limitations Indexes can be very useful, but they do have limitations. As data in a table is inserted, modified, or deleted, an index must also be updated to address any and all changes. This automatic feature requires additional CPU resources to process any changes to a table. Also, as a separate structure in its own right, an index can consume considerable storage space. As a consequence, care should be exercised not to create too many indexes but assign indexes to only those discriminating variables in a table. Because of the aforementioned drawbacks, indexes should only be created on tables where query search time needs to be optimized. Any unnecessary indexes may force the SAS System to expend unnecessary resources updating and reorganizing after insert, delete, and update operations are performed. Also, select one or more columns to represent an index that has a subset size of no more than 15% of the population data set. This is sometimes referred to as the 15% rule. Optimizing Where Clause Processing With Indexes A WHERE clause defines the logical conditions that control which rows a SELECT statement will select, a DELETE statement will delete, or an UPDATE statement will update. This powerful, but optional, clause permits SAS users to test and evaluate conditions as true or false. From a programming perspective, the evaluation of a condition determines which of the alternate paths a program will follow. Conditional logic in PROC SQL is frequently implemented in a WHERE clause to reference constants and relationships between columns and data values. To achieve the best possible performance from programs containing SQL procedure code, the SQL optimizer determines whether any available index(es) will perform better than if it were to use more traditional sequential data access. Many users incorrectly assume that an available index is automatically used with WHERE-clause processing, but this is not always the case. In fact, WHERE-clause processing does nothing more than influence the SQL optimizer to take advantage of an index. When the optimizer determines that an index will improve processing speeds, the index is used to direct activities related to data access. Otherwise, the SQL optimizer uses the more traditional, and default, sequential data access method with WHERE-clause processing. Conclusion Indexes can be used to allow rapid access to table rows. Rather than physically sorting a table, an index is designed to set up a logical arrangement for the data without the need to physically sort it. Not only does this have the advantage of reducing CPU and memory requirements, it also reduces data access time when using WHERE clause processing. As was presented, by adhering to a few important rules about creating indexes, SAS users can experience an improvement in a query s performance and processing speeds. References Lafler, Kirk Paul (2009), Exploring DICTIONARY Tables and SASHELP Views, South Central SAS Users Group (SCSUG) Conference, Software Intelligence Corporation, Spring Valley, CA, USA. Lafler, Kirk Paul (2009), Exploring DICTIONARY Tables and SASHELP Views, Western Users of SAS Software (WUSS) Conference, Software Intelligence Corporation, Spring Valley, CA, USA. Lafler, Kirk Paul (2009), Exploring DICTIONARY Tables and SASHELP Views, PharmaSUG SAS Users Group Conference, Software Intelligence Corporation, Spring Valley, CA, USA. Lafler, Kirk Paul (2008), Simple Rules to Remember When Working with Indexes, Proceedings of the Annual MidWest SAS Users Group 2008 Conference, Software Intelligence Corporation, Spring Valley, CA, USA. Lafler, Kirk Paul (2007), Simple Rules to Remember When Working with Indexes, Proceedings of the 1 st Annual SAS Global Forum (SGF) 2007 Conference, Software Intelligence Corporation, Spring Valley, CA, USA. Lafler, Kirk Paul (2006), A Hands-on Tour Inside the World of PROC SQL, Proceedings of the 31 st Annual SAS Users Group International Conference, Software Intelligence Corporation, Spring Valley, CA, USA. Lafler, Kirk Paul (2005), Manipulating Data with PROC SQL, Proceedings of the 30 th Annual SAS Users Group International Conference, Software Intelligence Corporation, Spring Valley, CA, USA. Lafler, Kirk Paul (2004). PROC SQL: Beyond the Basics Using SAS, SAS Institute Inc., Cary, NC, USA. Lafler, Kirk Paul (2003), Undocumented and Hard-to-find PROC SQL Features, Proceedings of the Eleventh Annual Western Users of SAS Software Conference. Lafler, Kirk Paul ( ). PROC SQL for Beginners; Software Intelligence Corporation, Spring Valley, CA, USA. Lafler, Kirk Paul ( ). Intermediate Software Intelligence Corporation, Spring Valley, CA, USA. 4

5 Lafler, Kirk Paul ( ). Advanced Software Intelligence Corporation, Spring Valley, CA, USA. Lafler, Kirk Paul (2002). PROC SQL Programming Tips; Software Intelligence Corporation, Spring Valley, CA, USA. SAS Guide to the SQL Procedure: Usage and Reference, Version 6, First Edition (1990). SAS Institute, Cary, NC, USA. SAS SQL Procedure User s Guide, Version 8 (2000). SAS Institute Inc., Cary, NC, USA. Acknowledgments I would like to thank Mary McCracken and Ethan Miller, Coders Corner Section Co-Chairs, for accepting my abstract and paper. I d also like to thank Rebecca Ottesen, Academic Chair and Marian Oshiro, Operations Chair for a terrific conference. Trademark Citations SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. indicates USA registration. Other brand and product names are trademarks of their respective companies. About The Author Kirk Paul Lafler is consultant and founder of Software Intelligence Corporation and has been using SAS since Kirk provides IT consulting services and training to SAS users around the world. As a SAS Certified Professional, Kirk has written four books including PROC SQL: Beyond the Basics Using SAS, and more than four hundred peerreviewed papers and articles. He has also been an Invited speaker and trainer at more than three hundred SAS International, regional, local, and special-interest user group conferences and meetings throughout North America. Kirk s current interests include serving on the sascommunity.org Advisory Board; contributing SAS- and SQL-related topics; writing and supporting a SAS Tips column called, Kirk s Korner of Quick and Simple Tips for numerous SAS User Group newsletters and websites; and sharing his fun-filled SASword Puzzles in SAScommunity.org. Comments and suggestions can be sent to: Kirk Paul Lafler Software Intelligence Corporation World Headquarters P.O. Box 1390 Spring Valley, California

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